"On 24th July 2015, Chrysler
announced that they will be recalling 1.4 million vehicles which they suspect
of software vulnerability in the Uconnect dashboard computed[1]
and is a potential threat for hacking. Two Security researchers Charlie Miller and
Chris Valasek hacked the car's entertainment system which was connected to the
mobile data network and controlled the car remotely. They showed that Cyber
security is a real treat to vehicles.

These days it is often talked and
written about connected cars and how it is going to disrupt the industry. The demand
for connected cars globally is growing at a fast pace. Customers wants to be
connected always and the experts predict that digital disruption in automobiles
have already begun. Projection shows up to 15 percent of new cars sold in 2030
could be fully autonomous[2].

Traditionally automobile
manufactured have focused on passenger safety and quality of the product as
their top priorities. During manufacturing process, the plant operators have
always identified component and process which will directly impact the safety
of the passengers. However, increasing use of advanced technologies like
telematics, autonomous vehicles, IoT have increased the risk of cyber-attacks.
Automobiles are as vulnerable as one's laptop or mobile as it is increasingly
getting connected to other IT devices.

When someone hacks a vehicle of
perform a cyber-attack, the hackers get into the vehicles' networks and controls
the electronic control units (ECU). This not only puts the drivers' personal
data on risk but also risks the passengers' life and safety.

In comparison to other
industries, automobile industries are way behind on the maturity curve in terms
of its preparation towards cyber defense capabilities[3].
According to Professor Andry Rakotonirainy from Queensland University of Technology's
Centre for Accident Research & Road Safety[4]
; the security protection on cars is virtually non-existent and one can compare
its level of protection to that of a computer way back in 1980s.

But they have started understanding
the importance of cyber security. In 2014 Jeff Massimilla was named chief
product cybersecurity officer of General Motors; a position never heard of in
an automobile industry.[5]
With increasing threat and risk, other OEMs will follow suit and recognize the
importance of cyber security as their vehicles become more connected and more
vulnerable.

More complex the product, more is the vulnerability. In some
of the high end models, it has become a combination of laptop and mobile with
multiple microprocessors[6]
and each will have its own software's with millions of lines of code. Each node
will be a point of vulnerability and a path for the hackers to get in and take
control of the vehicle.

As per a McKinsey report only 10 percent of the automotive
suppliers say cyber security ranks high on top management's agenda compared to
35 percent of OEMs. This data clearly shows the low importance and that the
suppliers are least prepared to adopt security measures in the product. Each
supplier has to adopt cyber security measure to protect the vehicle as whole.
Even if a single electronic component is vulnerable, the vehicle will get
affected since all are interconnected.

Finally, just like any other electronic device, ignorance of
users is also an easy path for hackers to get into the network. As vehicles
become more compatible and get connected to other devices, more entry points
are created. The kind of care that users take for online banking, similar
protections are required for vehicles in future.

As the OEM designs & engineers the vehicle, the should
take care of reducing the points by which a hacker can enter the network. This
can be done by securing the critical safety and control systems. This is called
Air gapping. Here, to ensure network security the computers will be physically
isolated from un secured networks like public Internet or an unsecured local
area network[7].
So in automobiles one could separate the passenger infotainment system from
other critical control system like brakes, steering etc.

The vehicle network system should have detection and alert
mechanism to inform the driver about a potential intruder into the system early
on so that the driver can take necessary action to stop the entry of a hacker.

Authentication and authorization is another area that needs
to be addressed in increasing the security. Online banking applications has
been widely using it, however adoption in automotive industry is still at a
very nascent stage. Using encryption and cryptography is the way forward to
address the risk arising due to access breach. Blockchain is an upcoming
technology in encryption and cryptography and several use cases will evolve in
cyber security area and automotive industry should keep a watch on its evolution.

While OEM designs electronic system, a manual override
system should also be designed for critical systems like Steering, Brakes etc.
In case of any hacking, there should be an alternate mechanical system which
can come into play during such scenario. The passenger or driver can switch to
a mechanical system whenever any suspicious activities is detected in the network.

Connectivity is a necessity for any device an individual
owns in this era of technology revoution and convergence. Automobiles is no different as it gets connected to multiple other devices and networks. This technological
disruption is inevitable and it is every OEM's responsibility to ensure safety of
the drivers and passengers who are using their product. Here, we are not just talking about
data theft, but a threat on the life
of an individual. We see that every company is investing heavily in latest technologies like telematics, autonomous vehicles etc. However, its adoption will depend on the
customer's confidence in its safety and security features. OEMs have to collaboratively
find ways to set up security standards which can be adopted across the supply
chain. OEMs and suppliers have to establish partnership with software
vendors and experts in cyber security to ensure security of their products and
keep the product up to date with respect to its security.

Introduction

A common occurrence we encounter
in dealerships is the customer being informed by the dealer/service agent of a
delay in procuring the spare part from the supplier or the OEM (Original
Equipment Manufacturer).

In spite of being an area of high
significance, OEMs have traditionally found it hard to forecast the demand of
spare parts accurately. Factors like complexity, erratic demand, large SKUs have continually thwarted the accuracy of forecast. On most occasions, lack of
proactive mechanisms to anticipate part failures lead to long waiting time for
a customer.

With the influx of Telematics
into the world of Automotive, accurate data on parts usage will be made
available for the OEMs, suppliers and dealers thereby improving the forecasting
mechanisms.

Spare parts market categories

The current spare parts market
can be split into two major categories:

1. OE Spares - These are spare parts which are sold by the OEMs
through their exclusive dealerships and are typically sold at a premium. These
parts are procured from suppliers and certified by the OEM as Genuine Spares.

2. Independent After Market (IAM) - The parts sold through this
channel are available at all spare parts stores. These are sold independently
by the suppliers but not certified by the OEM as genuine spares. Hence they are
cheaper than the OE spares.

Shortcomings of current forecasting techniques

Given the two different types of
spare parts market, the next logical question would be, how demand is presently
forecast. With the demand being need-driven, companies currently use any one
of the traditional forecasting methods or a combination of a few to forecast
their demand. 'Poor data quality costs
around $600 B US dollars to US companies each year' highlights a statistic.

Albeit having some
well-defined methods, forecasting is still a tough equation to crack owing to the number of assumptions made during the process. With each part
having its own demand pattern, it becomes increasingly difficult to forecast,
thereby impeding its accuracy. Owing to this, dealers maintain large SKUs
(Stock Keeping Units) fearing the opportunity cost due to lost
sales. This overstocking not only leads to over usage of real-estate space
apart from hampering working capital of the dealer but also result in
piling up of obsolete stock. On the flip side, maintainingvery few parts that have a constant demand would
often lead to stock-out situations and customer dissatisfaction.

A mere increase in
serviceability levels from 95% to 97% would increase the inventory levels by
two times. -Based on inventory
level calculation.

Magnitude of 'cost of stock' is very high as it leads to loss of saleand customer good will.Striking a
balance to maintain an optimum level of inventory and desired service level, is
an area where every automotive player is looking for solutions.

Figure 1:Advantages of connected cars over unconnected cars [4]

Telematics as an enabler

With the technological
advancements making automobiles more connected than ever, vehicles fitted with
electronic parts and sensors are able generate huge amount of data. Breakthrough
inventions in areas like Cloud Storage, Connectivity speed, Big Data Analytics
are providing the means to store and process the data in a quicker and
efficient manner. Similarly, sensors and other devices required to capture data
have also become more affordable making the process simpler and easier

The type of data that vehicles on
road can now transmit, range from overall performance indicators to the health
condition of parts in use. Availability of this 'in-vehicle' data can
dynamically alter the way the parts forecasting is done. It will not only
improve the accuracy of forecast, but also help in ensuring 3R's (Right parts
at the Right place at the Right time), the most sought after attribute by the
companies. One can never guarantee the 3R's with the traditional forecasting
methods as they work on the premise, "Future can be predicted by looking into
the past", which most often has an element of error associated with it.

Figure 2: Benefits of vehicle connectivity [2]

The processed data can help
companies gain insights on multiple parameters such as driving pattern,
condition of the parts, and performance of the vehicle. This can play a great
role in enhancing the customer experience. Monitoring the health of the parts
in the vehicle can help a customer proactively schedule an appointment for
replacement of the part and prevent unprecedented breakdowns.

For
instance, consider a typical case of a sedan being continually driven on a
hilly terrain resulting in brake pads wearing out sooner than the prescribed
mileage/time frame. Access to this data can help OEMs gain insights and
proactively store more brake pads in dealer locations on hilly regions. The
data will also enable them to factor in the local geographical conditions when
fixing the durability of the part.

This real-time data can help
stakeholders get an idea of the kind of parts that are required to be stocked
at the dealer locations. Accurate usage information could aid OEMs to do a
targeted distribution aiding in optimization of inventory levels at dealer
locations. Metrics like Inventory

Turnover Ratio (Times the
inventory has been turned over in a particular period) will also improve from
an OEM perspective due to the accuracy of the forecast.

The availability of data will also
improve the communication and collaboration between the Tier I suppliers and
OEMs due to the increase in transparency across the supply chain right from the
dealer to the supplier, significantly reducing the buffer at each end.
Suppliers functioning upstream will be able to efficiently plan their
production schedules since the actual number of parts that are running on road
and the number that needs to be replaced are available at any point of time,
thereby drastically reducing the bull-whip effect.

Another major functional area,
where 'in-vehicle' data can help reap benefits for the OEMs, is logistics. The availability of real time data will bring
down logistics costs drastically. Knowing what kind of part is needed at which
place will help in considerably reducing the inter dealer transactions and
ordering costs. Only a small buffer would be required to cater to unforeseen
incidents like accidents.

Warranty management is an
additional space where 'in-vehicle' data can provide a sizable benefit. Mining
of real time data for key insights like driver behavior, handling, maintenance,
location and other details will help in OEMs handle the warranty campaigns
efficiently. It will help OEMs approach concerns like NTF (No Trouble Found)
& Invalid claims in an informed and better manner as it saves precious time
and money spent on unfruitful negotiations. Researches show that access to
'In-Vehicle data' can save warranty claim costs by 25% and also bring down
recall costs by 35%

Conclusion

In the tightly contested space of
automobiles, where OEMs are trying hard leaving no stone unturned to occupy the
TOMA (Top of Mind Awareness) of the customers, leveraging the 'in-vehicle' data
captured through telematics in the parts supply chain space can reduce the lead
time across the chain from dealer to supplier significantly. It will also aid
in improving the satisfaction levels of the customers, providing the much
needed competitive advantage

Automotive Original
Equipment Manufacturers (OEMs) are increasingly looking up to big data
analytics for solving many of their business challenges and staying ahead of
the competition as the data available at their disposal is increasing at
exponential rates. The data collected from the vehicle, along with other
data owned by the OEM across various enterprise functions, and data collected
from external sources can provide valuable insights about the customer and
vehicle - two key elements that determine the fortunes of any automotive
company. Automotive companies are trying to maximize the value delivered to a
customer by leveraging the collected data for service & product offerings,
customized customer experiences and additional revenue through a deeper understanding
of customer's attitude and behavior. Analyzing customer behavior provides
valuable insights into aspects such as brand loyalty, customer satisfaction,
customer preferences, sales and aftersales behavior, price sensitivity and
propensity to buy (accessories, warranty plans, new vehicle and subscriptions).

Leveraging Automotive
Enterprise Data

Data analytics presents
a plethora of business opportunities for Automotive OEMs. A typical Automotive
OEM with fairly advanced Telematics capabilities and IT systems gathers a good
repository of information that can feed in as inputs for analytics. The data
available with an Automotive OEM can be broadly classified into three
overlapping categories - vehicle data, customer data and external data as
mentioned in the diagram below. The classification is based on the primary
entity to which the data is attached. For example, a customer's social media
activity is tracked and stored. Hence this can be considered as customer data.
Similarly the ECU and sensor data is generated for the vehicle, so it can be
considered as vehicle data. In some cases, there are more than one entities
associated with the data. For example: Point of sale data may include
incentives offered to the customer for the vehicle. This can be considered as
both vehicle data as well as customer data. This overlapping circles in the
diagram signifies that there is overlap in the classification of data by
entity.

Vehicle data covers the
complete lifecycle of a vehicle through stages such as Manufacturing, Sales and
Aftersales till the end of a vehicle's life. Data that can be collected
comprises of point of sale data, Factory master data, ECU and sensor data, part
wear & tear and failures, warranty claims, recalls and service & repair
data.

Of all the data sources,
Telematics data plays a major role by providing a wealth of valuable
information from the Electronic Control Units (ECU) and Sensors, Navigation,
driving behavior, telematics products usage, data from other devices, vehicles
and cloud.View image to see the types of
data available with an Automotive OEM.

There is a wide range
and ever-expanding list of use cases of the Telematics data such as usage based
insurance, driving assistance, predictive maintenance, personalized and
location based marketing and several other new products and service offerings
that are being talked about or implemented by various Automotive OEMs.

Outlined below are a
couple of interesting analytics possibilities about how Telematics data can be
leveraged to predict customer behavior in two important business areas - Sales
and Service.

Predicting New Car
Purchases

When would a customer be looking out for the next
vehicle purchase? Can data analytics predict a customer's inclination for a new
car purchase? These are some questions for which Automotive OEMs and
dealers are looking for an answer.

Figure 2: The Illustration shows a
customer switching brands due to an unsatisfactory experience at a dealership
for new vehicle purchase inquiry. The customer expresses anguish in social
media and visits competitor dealers to look for alternate options. Using data
analytics, this customer could have been retained in the same brand family.

With best-in-class
technology and big-data processing capabilities, machine-learning
models can be built to determine the propensity of a customer to buy the next vehicle
based on various data points available. Age of the vehicle, wear
and tear, miles driven and customers' past ownership history could be some of
the influencing factors. The negative customer experiences that could be the
tipping point for brand switching could be understood by analyzing call
center call sentiments, dealer interactions or social media activity. OEMs
could track the navigation patterns of the customer and determine if the
customer is shopping around for a competitor brand in pursuit of the next car
purchase. Applying human feedback to the machine learnt recommendations will
help strengthen the prediction results.

Service Retention

The data from the ECUs
and sensors give a good indication of the health of the vehicle and can be used
to build intelligence around analyzing the patterns of individual customers in
response to a failed part, and their subsequent visit to a repair center to get
it repaired. Subsequently, the OEMs can send notification alerts or have the
dealers reach out to the customers proactively for maintenance and repair
services before the customers get these issues diagnosed and serviced
elsewhere.

Figure 3:The Illustration shows a customer who typically
goes to different repair centers depending on nature of the problem with his
vehicle. In this case, the OEM or Dealer can reach out to the customer with
targeted promotions for parts and services for which the customer would never
visit an authorized dealership.

Competition and
Collaboration

Other than the
Automotive OEMs, the other Telematics ecosystem players are also be keen on
gaining a share of the data and leverage it for building analytics use cases.
Google's Android Auto and Apple's CarPlay are good examples where the ecosystem
player has an opportunity to gather a lot of in-vehicle data. Another example
is Verizon, who provides in-car connectivity to some Automotive OEMs, also has
an aftermarket product 'Hum' that collects vehicle diagnostics data. There are
other connected car startups like Zubie, who have forayed into multiple areas
like insurance and onboard diagnostics and are collecting large volume of
vehicle and customer data.

However, the ownership
of the customer data and terms of conditions of usage are decided by
contractual agreements and data privacy principles. Customer data cannot be
collected, stored and leveraged in personally identifiable form unless it is
communicated clearly to the customer and the customer provides consent for the
same. OEMs while working with Telematics partners, will have to be careful in
managing the contracts and data sharing agreements to ensure that they don't
relinquish control of the data to their partners or do not invade customer's
privacy.

With the increasing
penetration of Apple's CarPlay and Google's Android Auto in the Car
Infotainment space, the competition between Telematics ecosystem players and
the Automotive OEMs will become more intense with respect to gathering
in-vehicle data and leveraging it for analytics use cases.

Though Google and Apple
have advanced technology capabilities, the availability of complete array of
automotive enterprise data (mentioned in the diagram) provides a unique
advantage for Automotive OEMs to dominate the data analytics space. However, as
the competition is intense, agility and ability to adapt to changes in a
marketplace are some of the key success factors in maintaining a competitive
edge.

Automotive OEMs may be
cautious in their approach towards Google and Apple, but are partnering with
other technology and consulting companies to accelerate their journey towards
data analytics. Recently, Toyota launched a new company Toyota Connected Inc.,
in partnership with Microsoft to significantly expand the company's
capabilities in the field of data management and data services development.
Ford partnered with IBM to add cloud and big data capabilities
to its Smart Mobility initiative that aims to advance connectivity, mobility,
and autonomous vehicles.

Key Challenges

The race to building
cutting-edge analytics solutions is however not as easy as it may appear.
Automotive OEMs will have to overcome several challenges in their journey with
respect to acquiring data, storing data, and leveraging data for analytics.

Challenge: The customer has the freedom to download an application
provided by a third-party telematics services provider and the OEM has to share
the vehicle related data with the customers and these third party service
providers based on customer's consent.

Cick on the link to view the architecture of a telematics
platform that can be used by automotive OEMs to provide a seamless integration
between the vehicle and the cloud based telematics services' applications. View image

Challenge: One of the other challenges is the utilization of available data.
Many a times, data is gathered without keeping the end goal in mind and a lot
of data is not utilized for any meaningful analytics. This results in wastage
of manpower and computing infrastructure. Michael Gorriz, Chief Information
Officer, Daimler rightly said that "Big data analysis is an important area
for Daimler, but generating large volumes of data is not a goal in itself. More
important is to use the data to create business and customer value".

Also, due to the immense
competition, OEMs have to innovate faster to keep pace with or to move ahead of
competition. Agile execution of IT initiatives is one of the key success
factors in order to achieve this. Slow decision making and execution of IT initiatives
will result in losing relevance in a fast changing market.

Conclusion

Automotive OEMs are
collecting huge volumes of data from the vehicle, ecosystem and various other
sources. The real potential of the collected data can be realized only with a
clear vision of the data analytics strategy. Identifying the right business opportunities
that create value to all stakeholders, investment in the right analytics tools
and resources, keeping pace with market trends, controlled cooperation with
ecosystem players and technology companies, agile execution of initiatives and
managing the challenges mentioned in this article are some of the key factors
required to succeed in this highly competitive space.

The concept of
connectivity in the automotive industry was pioneered by General Motors, when
it introduced emergency assistance with OnStar in 1995. The concept was connectivity,
which was previously limited to infotainment, has evolved to remote
applications, safety and security, vehicle intelligence, eco driving, vehicle diagnostics and secondary services.

Fig: Evolution of Connected Cars Features

To

captivate the
nextgen buyers, Automakers are now converting their vehicles into smart
vehicles on wheels. Gartner predicts that 250 million vehicles will be
connected with a 67% increase in the number of installed connectivity units by
2020. With an engineering legacy, automakers are now partnering with Technology
Service Providers (TSPs) to reduce time-to market and increase the car maker's
footprint. If they fail to do so, in the long term, automakers could end up as
hardware suppliers to tech giants such as Apple and Google.

Factors Forging Partnerships

Automakers are
investing in technologies related to vehicle-to-vehicle (V2V),
vehicle-to-infrastructure (V2I) services, and fleet services to engage the millennial.
Most of these services are realized by partnering with Technology Service
Providers (TSPs). Our studies of the investments made by OEMs in Connected Car
Services, suggest that the key influencers to forge partnerships are- advanced driver assistance system (ADAS),
semi-autonomous driving (SAD), remote applications, single mobile platform that
manages the entire digital automotive experience, intuitive and safe access to
infotainment, urban mobility and secondary services (usage-based insurance,
toll collection). While a majority of these shifts demand collaboration with
technology companies, trends such as urban mobility and secondary services
require partnerships with fleet service providers, city and government
administrators that provide infrastructure services, and research partnerships
with universities.

A
few examples of such partnerships: General Motors' partnership with Shanghai
OnStar and Didi Chuxing - China's largest car-hailing app - to support
expansion plans in China; Toyota's partnership with City of Grenoble,
Grenoble-Alpes Métropole, Cité lib and the EDF Group (an electric utility
company in France); BMW's investments in MyCityWay and Parkmobile. From an
infotainment perspective, multiple automakers have partnered with Google,
Apple, and MirrorLink to develop a single mobile platform. Until 2016, 35 auto
brands have tied up with Android Auto, 41 with Apple CarPlay, and 12 with
MirrorLink.

An unlikely
avenue that compels automakers to form robust alliances across industries is
cyber security. Ransomware designed by professional attackers, could be
the most serious form of threat. Consequently,
automakers are addressing these issues by opening up information sharing
platforms, with security agencies, hackers and other OEMs. Automotive
Information Sharing and Analysis Center (Auto-ISAC), German Cyber Security
Organization (DCSO), and GM Vulnerability Disclosure Program with HackerOne are
some notable collaborations. Auto-ISAC is a collaboration of Automotive OEMs
that promotes transparency in sharing cybersecurity threats and
countermeasures. DCSO is a holistic effort to address cybersecurity across
industries in Germany.

Constraints Around Partnerships

Some of the key
challenges faced by the automakers in forming strategic partnerships today are:

Partner explosion due to regional complexities: Enabling secondary services such as car sharing, usage based insurance, etc. will require OEMs to spend considerable effort in developing local alliances. Based on the area covered, multiple partners for a single region, and service, is a possibility.

Long lead times to enable services: Scouting for the right regional partner and arriving at consensus on liabilities, could entail significant lead times. Unless tackled swiftly, OEMs could lose their first mover advantage and run the risk of becoming market followers than trend setters.

Inability to pass on the cost to the customer: While the consumer desires a world of functionalities, his willingness to pay for the same is not proportionate. Automakers have to absorb the cost of enabling digital features. E.g.: The total price of Mercedes E-Class increased by €1,654 between its 2010 and 2015 digital packages while the cost of adding connectivity options was €7,0002. OEMs cannot lose sight of indirect costs incurred due to strong vendor management programs and legal teams to enable these services.

Strategic Failures: OEMs are investing millions in R&D towards services like urban mobility. Inability to predict the pioneering services with geo-specific variants and converting investments into viable products and services could lead to heavy losses.

Brand Management: Partnering with third parties for services with possible undetected vulnerabilities in the products, such as safety, will ultimately still be the responsibility of the OEM in case of recalls & lawsuits.

Trends

With burgeoning
telematics services and complex TSP ecosystems, following are some of the
trends we may expect to see in the near future:

Bundling Telematics Packages: Given most of the telematics revenue is expected to flow from the customers of the passenger car segment, competitive pricing is key. If manufacturer installed options are offered at premium prices, the customer could very well chose a third party add-on solution, available at a much cheaper rate. Eg: Navigation devices are available in the market for €180, as compared to a €600 embedded option offered by the manufacturer2.

Traditional technological providers reinventing themselves: TomTom, is a classic case of an organization that transformed itself from a portable navigation device manufacturer into a supplier of embedded telematics equipment. Proliferation of smartphones, that left portable navigation-only devices obsolete, forced the supplier to foray into the telematics business for survival. Today, major OEMs like BMW, Daimler, GM, Volkswagen, Toyota and Volvo use the platforms and offerings from TomTom in one way or the other.

Cyber security: Besides a collaborative approach, automakers could engage with independent security validation services that review application code and provide unbiased views on the security features developed and closed out with their partners.

Consolidation of Telematics Service Providers: Today, most TSPs specialize in services that pertain to one or two areas of Connected Car Services like infotainment or vehicle diagnostics. Automakers will look at enabling services across the spectrum. Instead of direct partnerships with multiple TSPs across service lines, they will look to minimize the overhead of supplier management. TSPs that provide a consolidation of services and in turn manage the tier 2 and 3 suppliers, will be the go-to partners in the future.

Conclusion

Global
penetration of automotive telematics is expected to grow, from the current 48%
to 62% by 2020, in the area of Vehicle Diagnostics. Safety & Security, is
expected to capture more than 60% of the telematics services3. The evolution of
partnerships is observed the most, in the areas of Urban Mobility and
Infotainment.

With mobility services
touted to be a profitable source of income for automakers in the next 5-10
years, it remains to be seen how the automakers will pool together and convert
their R&D investments, partnerships across ecosystem players, regulations
and understanding the consumers' needs (and services they are willing to pay
for) and stay ahead of their competitors and/or afford to retain their spot.
Investment in enabling these services and prudence are inevitable.

In the short
term, connected cars services will act more as a product differentiation
strategy rather than a source of revenue. In the long term, it will help open
up new digital revenue streams through service offerings such as urban
mobility, infotainment, and concierge services.

References

"Gartner Says By 2020, a Quarter Billion Connected Vehicles Will Enable New In-Vehicle Services and Automated Driving Capabilities", by www.gartner.com

]]>http://www.infosysblogs.com/thought-floor/2016/11/connected_cars_forging_new_parterships.html http://www.infosysblogs.com/thought-floor/2016/11/connected_cars_forging_new_parterships.htmlTue, 08 Nov 2016 06:17:52 +0000Future of eCommerce in India and its significance to a Common Indian Customer

Having noticed a tremendous innovation and growth
in the Digital Transformation space, I wonder what it would mean to be a normal
Indian consumer, who is now experiencing these changes. In this blog, I attempt
to understand and bring forth the perspective of their experience on these
wonderful E-commerce sites.

]]>http://www.infosysblogs.com/thought-floor/2015/10/future_of_ecommerce_in_india_a.html http://www.infosysblogs.com/thought-floor/2015/10/future_of_ecommerce_in_india_a.htmlWed, 14 Oct 2015 12:41:00 +0000The + Service opportunity for Industrial ManufacturingIndustrial manufacturing is typically a
low-volume high-value long-term play. The potential high value of each sales
transaction is counterbalanced by a generally protracted sales gestation
period. And post commissioning, most of these capital intensive solutions have
impressively enduring lifecycles.

In case you haven't heard, the world is going to collapse
soon! Well, not really but scientists and experts from UK have predicted that,
at the current rate of data consumption, the internet will collapse in about 8
years. Wow! That's as good as the end of the world for the digital dreams we
all had.

Which brings me to my favorite subject - Internet of Things
(IOT). This premonition about the 'capacity crunch' of the internet will spell
doomsday for companies betting on IOT enabled products and services since they
will rely heavily on the internet. Real-time sensor-data transfer over the
internet is the backbone of the connected world and one that will bring immense
transformation to the way we use products and services. Gartner predicts 20
billion devices to be connected to the internet by 2020. This figure will only
increase exponentially beyond 2020. All this internet activity due to IOT will
only accelerate the downhill spiral towards the internet capacity crunch. If
there is a capacity crunch in the offing, what happens to all the IOT use
cases? With no regulations or regulatory bodies, how does one optimize usage of
available internet capacity? With much to lose, I think it is time to introspect
and determine what could possibly be a more practical choice for customers to
get the benefits of IOT while still doing their bit to delay the doomsday.

I foresee a subdued future for IOT rather than the
enthusiastic hurrah we hear from most analysts. Let me explain what I mean by
'subdued'. I believe that the theory of a connected world will remain just that
- a theory. (Well, at least in the short term until we are able to figure out
what and how to handle the entire IOT ecosystem and that too in an unregulated
arena.) Gartner may be right about the number of devices being connected by
2020 but when it comes to transmission of data (and here's where the bandwidth
crunch comes into play), it may not be practical to have all the connected
devices to send data at all times. In fact, the rate and type of data to be
transmitted will be controlled by the biggest equalizer in business - the
humble customer or end user.

I think it will be futile and in fact amateurish for
companies to just put up a few sensors on their products and start relaying the
data over the internet. Not every customer would be ready to pay for this
service especially if you are unable to show her the value of doing this
activity in real time 24x7. I predict a bouquet of services to be offered by
corporations to its customers to choose and determine which option best suits
their (customer's) needs. Let's take an example of a smart refrigerator. Not
all customers would be able to afford their refrigerator monitored for its
health 24x7 since that would entail paying for a higher internet plan. Some may
opt for an option wherein once the refrigerator starts giving trouble, the
customer will be alerted on their smartphone and they will then have the
ability to trigger a health check from their phone app. This app will finally
push the logs (findings in software code) from the smart refrigerator to the
service company over the internet for the technicians to analyze and revert
with the best solution. The solution could either be an over-the-air software
update or a field technician visit to check and rectify the problem at site. In
any case, it will mean that the service company will have data upfront to
analyze and decide before any visit.

The higher end customers may go in for predictive maintenance
type of service packages which will help prevent failures but for those who
cannot afford such premium services, they could at least go for these intermediate
solutions. So how does this help in capacity crunch? Voila! - Optimized
transfer of data over the internet from these connected devices. These assets
will be part of IOT and hence connected; they will support customers to control
when to send data and hence control costs and lastly, customers will be in
better control of their data - thus addressing the data privacy concerns of
many.

Internet doomsday or not, customers will challenge the IOT companies
to come out with innovative options that will make the technology economically
feasible to all. And it's upon us to make that happen. It will be disastrous
for all players to thrust connected devices without providing options on how to
optimize internet bandwidth. What do you think is going to happen in the future
of IOT?

Social Media revolution has enhanced
the way we communicate with our acquaintances and also helped improve the
efficiency of conducting business. There is not a single day when we don't hear
news about Social Media or use them. Overall it enables individuals to receive
update from friends, share videos and Photos. For business, it helps them to
build and maintain new relationships.

This article embodies the architectural thoughts on Internet
of Things for Architects and developers. The aim of this paper is to provide a
base architecture that covers challenges and main requirements of IOT projects
and systems - devices, server side, cloud based services, third party
integration that interact with and manage the devices.

1.1What is Internet of Things?

The
Internet of Things (IoT) is a scenario in which objects, animals or people are
provided with unique identifiers and the ability to transfer data over a
network without requiring human-to-human or human-to-computer interaction. IoT
has evolved from the convergence of wireless technologies, micro-electromechanical
systems (MEMS) and the Internet.

A
thing, in the Internet of Things, can be a person with a heart monitor implant,
a farm animal with a biochip transponder, an automobile that has built-in
sensors to alert the driver when tire pressure is low -- or any other natural
or man-made object that can be assigned an IP address and provided with the
ability to transfer data over a network. So far, the Internet of Things has
been most closely associated with machine-to-machine (M2M) communication in
manufacturing and power, oil and gas utilities. Products built with M2M
communication capabilities are often referred to as being smart. ( smart label,
smart meter, smart grid sensor)

1.2Devices

The simplest devices have embedded controllers - they have no operating systemDevices with 32-bit system that can support OS -
such as LinuxDevices with 32 bit/64 bit computer platforms
such as a wearable watch that can connect to internet and support 2 way
communicationDevices that communicates to gateways; these
gateways perform filtering, aggregation, event processing

The way devices communicate with gateways/internet could be
based on:

Ethernet, WiFi using TCP/IP or UDP, MQTT, http, CoAP

UART, SPI/ I2C

Near Field Communication(NFC)

Zigbee and mesh networks in RF, blue tooth

Modbus

Low Power Bluetooth technology

SRF

2.0 Challenges

We have to address the obstacles to the connection to the devices - Firewalls, Network Address Translation (NAT) and other obstacles on the way.

There could be issues in connectivity of devices due to internet connectivity, battery life, RF interferences, simply being switched off, physical security/damage etc.,

There is plethora of protocols, vendors in this space. Inter-operability among these and derive the required data from these could be a challenge.

The
data from the devices is accessed over various protocols as mentioned above and
protocols with lowest overhead over payload - MQTT and CoAP are clear winners
on this account.

We
can have an implementation of Agent Hub running in the device/gateway layer,
which would collect the data from devices and send it over to a Central
Registry (which is the case with Bosch M2M platform) in the ingest layer.

We
need a filter, adapter, transformation are part of data ingestion; Complex
event processing (CEP), Business process Modeling (BPM), Business Rules
Modeling (BRM) are in the Processing layer. A pub/sub model is best for
handling data at this layer. Choices could be ActiveMQ, RabbitMQ or cloud bases
offerings such as SQS. CEP is available in many flavors - open source tools
such as WS02, ESPER; enterprise tools from Oracle etc; also, Storm/Spark from
Hadoop world. Data in flight Analytics using R or any other similar tool can be
done in this layer. Volume/Variety will decide the selection of tools in this layer.

4.3 Data
Storage and Access Layer

SQL
and NoSQL data bases are candidates for storing data. Depending on the volume
HDFS can be used as well.

Recommended
data access to the consuming applications is over REST API. This layer of
abstraction enables access across different data sources.

he Quality of Service is across all the layers - it should support non-real time, soft real time, hard real time depending on the application requirement. Architecture should support measuring the latency, data loss, ability to handle duplicate data, late arriving data, identify error in data. Instrumentation should be provided in all the services in the system that is capable of reporting the health, resource utilization, efficiency etc.,

4.6
Security

Security
risks associated with using inherent internet and risks that are associated
with IoT devices should be addressed. Best practices such as encryption, Identity
and access management with OAuth/OAuth2 (tokens rather than username/password)
are suggested. XACML based Attribute/Policy based Access control are
appropriate.

5.0 Conclusion:

This article covers the overview architecture of internet of things. We will elaborate on the individual layers of the architecture in the coming articles.

]]>http://www.infosysblogs.com/thought-floor/2015/02/pov_on_architecture_for_intern.html http://www.infosysblogs.com/thought-floor/2015/02/pov_on_architecture_for_intern.htmlInnovation in ManufacturingFri, 13 Feb 2015 11:02:41 +0000The Re-dawning of Business IntelligenceThat the Business
Intelligence world is being disrupted with new technologies is now common
knowledge. However, very few businesses & their BI groups have a holistic
view and roadmap to embrace this
change. All have few specific new capabilities in mind and here is an
opportunity to apply the Infosys 'New and Renew' Strategy to enable BI in your
organizations take the next leap.

So, firstly let's
assess what are we hearing from various stakeholders and the wider BI market:

Our Customers: We need BI to be agile, responsive,
trustworthy, cost efficient, easy to adopt and make the right strategic
business impact quickly

Infosys Experience
from Engagements: Need to Reduce time to insights, bring in some unique assets
to accelerate programs, Align customers to industry best practices and need
for clear engagement charter in terms of business value and capabilities within
an agile delivery model.

Industry Analysts: Analysts like Gartner, Forrester emphasize need for different pricing models, expand BI usage thru' the enterprise,
leverage cloud/big data/mobility/advanced visualization etc. They expect avg. BI market growth to
be 10% ; 70% of which will still be IT controlled; Analytics to command 20% of
those budgets and rest on Query/integration
and reporting.

Given these key
learning's, the new vision at Manufacturing BI is 'To transform our customers
from today's data driven to Analytics driven Enterprises enabled by Rapid,
Deep and Actionable Insights'.

In order to enable
'Rapid, Deep and Actionable Insights', the following offerings are being
planned:

Analytics Driven Enterprises: The goal is to
help enterprises transform from traditional data driven to analytics driven
organizations. This is to be enabled by an Analytics adoption framework that
helps make the right analytics investments that matter, 'Leverage-your-data' initiatives to take a deep look at available data & innovate to make
strategic use of it and Predictive & Descriptive modeling services driven
actionable insights for Manufacturing & Hi-Tech relevant areas like Supply
chain optimizations, Personalized customer service, sales, marketing and
finance analytics functions.

Amplified
Data Warehousing: Existing data warehouses augmented with Hadoop based
platforms to reduce turnaround time for multi-structured, high velocity datasets
needed for insights. This can also be leveraged to reduce the fast escalating
cost of data warehousing.

Proactive service maintenance is
not just limited to preventive maintenance but it is also includes predictive maintenance.
Service management is usually associated with negative experience as customer
contacts service provider when product has some issues. But it can be turned in
to positive experience if services are handled carefully and promptly, which
can result in lesser asset down time and faster service resolution. That's why,
it can be an opportunity for service provider to convert bad customer experience
into a good experience. Of course, it is not easy task and risk is always high
as if service provider is not able to provide better service, customer is gone
forever and he may provide negative feedback for your products/services.

Every one of us has had that
tingling feeling at the back of our necks while trying to reach to our car in
an isolated area or in the basement of a shopping mall or in an expansive
parking lot. The fear of someone lurking in the shadows or an anticipation of a
person springing on to you from the dark makes one either hasten their pace or
to reach out for the pepper spray can in their purses. We all suffer from this
fear of the unknown and one can only be prepared and alert to prevent one from
happening.

Wikipedia defines carjacking as
an 'armed assault when the vehicle is occupied'. And this is more dangerous
than a vehicle theft purely because the occupants are in danger of limb and
life in carjacking cases whereas plain theft may only be a material loss. There
is no knowing what may happen to a victim of a carjacking and hence one should
take precautions at all times.

Hopefully, cars of the future
will be more than helpful to deter such situations but technology is at hand
already through connected cars. A connected car is one that is always connected
to the internet and allows data transfer between the car's sensors and the
cloud. While there are a number of use cases for connected car, I think we can
add one more to that list by using it as a deterrent to carjacking. Simply put,
a car can be triggered to take pictures of its immediate surroundings and relay
it to a database in the cloud in real time.

Let me explain more on this. Say,
you get into your car and as you are about to start the engine, you see someone
approach your car door in a threatening way. You press the panic button on the
steering wheel or on the door panel. This will trigger the cameras on the door
sill to immediately start taking pictures with LED flash. Once taken, the
pictures get automatically uploaded into a secure website for future reference,
if required. An alarm will also get triggered about the incident (activation of
panic button) which will result in a call back given to the car to check if
everything is okay and if the incident was true or accidental.

Car OEMs can provide this as
additional features for safety or it could be also provided as after-market
options. The cloud storage would definitely be provided as a subscription based
service as an additional revenue model within connected car program. Customers
could also operate their account to view or delete old history and other
details. It would also be a cool way to take Selfies using your car!

One would need the following (at the
least) to make this happen:

·Cameras with LED flash to be installed on the
door sills. With smartphone technology development, the camera sizes have gone
smaller and with High Definition features, the picture quality has become
sharper. The LED 'flash-in-your-face' may also deter the weak hearted crooks
from carrying out their planned assault and has its own benefits.

·A panic button feature would be required on the
steering wheel or on the door panel. This can be designed based on research for
most accessible position in such situations. It could be in one or multiple
locations.

·Internet connectivity within the car. Car
companies are already working on getting a lot of connected car features into
modern cars today.

·A secure database on the cloud to upload the
pictures taken along with geo location and time. The upload should happen in
real time so that there is no chance for anyone to prevent it from being
stored. The pictures should also not be stored locally within the car as it
would lead to damage of the car and harm to the victim. The event could also
trigger storage of additional important data after the panic button is
triggered viz.engine condition (on/off)
for next 30 min, driving pattern, driving speed post event, etc. Algorithms can
be run in real time to check if car is moving in a direction other than usual
routes or if the driving pattern is different from the car owner's for gaining
additional insights into whether the car is driven by the owner or the
carjacker.

·A call back to the car can also be done to check
on the condition of the owner. A pre-programmed code word could be defined to
inform the police or security that the response is under duress. This will be
helpful under certain situations as well.

I agree that this will not be
able to prevent carjacking but if this facility was available, then it would
only make carjacking a difficult career option for crooks. With more such
anti-carjacking features, I hope one day it will be lot safer to drive a car.
Obviously, autonomous or self-driving cars will definitely bring in more safety
options but until then we will need interim solutions to deter carjackers of
this world. Drive safe, be safe!

Green, orange, red! The
origin of the humble traffic signal is not entirely known for sure but it is so
ubiquitous on our roads that its existence and its intentions are taken for
granted. After all, the signs are meant to be easy to understand for anyone
using road infrastructure. In some places it could be just the color of the
lamp whereas in some others it would be arrows to indicate direction as well as
instructions (to stop or to go). But all this is likely to change with Internet
of Things (IOT).

We all know about IOT and
how it is going to transform everything around us. In fact, at Infosys, we
believe that IOT will have a far larger impact on our lives as compared to the
impact from computers or the internet. This means that all the ubiquitous yet
mundane 'things' around us will soon start getting intelligent with sensors and
one will be pleasantly surprised to see the value add it will start bringing once
they are connected to each other and to the network. Same goes for traffic
signals as well.

Consider the IOT applications
related to the automotive world - Connected cars, Vehicle-to-Vehicle
connectivity, Vehicle-to-Infrastructure connectivity, etc. All these are
evolving and all stakeholders, from auto OEMs to governments to universities to
technology solution companies like Infosys, are partnering on creating feasible
and sustainable proof of concepts or pilot projects, focused on making the
driving experience richer, faster, safer and greener. As part of IOT use cases
'on the road', an important one is around faster navigation through a traffic
prone area using a combination of telematics data and GPS navigation. What it
states is that if there is a traffic jam ahead, the intelligent car will be
able to 'sense' the same and take a detour to avoid (or add to) the congestion
ahead. All use cases have been from an individual car perspective. But I am
looking at this differently.

I predict that if the car
can have this intelligence, then so can the infrastructure as well. If the road
ahead is congested, there is no point of adding to the woe by leading more vehicles
into the same zone or area. It makes more sense to let the congestion resolve
while directing incoming traffic to alternative routes. The density of car and
hence data from these cars will let the traffic management system (TMS) decide
on whether to accept any further incoming traffic or not. Based on this
information, the TMS will be in a continued stage of 'red' signal and intensify
the signal operations on alternate roads to clear as much traffic as possible. However,
the impatient driver will want to know more about an abnormally long 'red'
signal. And hence, the TMS will have to devise ways to communicate the same at
the congested entry junctions. Navigation systems will definitely throw up the
message but the traffic signals will have to adapt to this new information and
display a sign or a modified form of signal to indicate the congestion ahead. A
simple red will not suffice and it will have to signify a more meaningful
message to drivers at the junction who are not being allowed entry and being
diverted.

Imagine you are in the
left lane to turn left and it has maxed out due to the congestion. To take a
detour, the left lane drivers would have to be accommodated by the TMS into
alternate lanes and roads. For this to happen, TMS rules as well as driving
laws will have to adapt and change. Else, the entire idea of IOT and connected
cars enriching life on the road will go for a toss and not make a positive
impact on driving experience. This is a big change that transport authorities
will have to discuss along with road safety experts and TMS providers. I
believe this is an unexplored area that will further evolve the humble traffic
signal. So when in a few years, you see the change in the signaling system,
remember that you read it first here. Drive safe!